Custom AI development Switzerland
Custom AI Systems for Swiss Businesses
Off-the-shelf AI tools are useful, but many business problems need systems that fit existing data, workflows, users, and constraints. Fanktank designs and builds custom AI systems around the real operating environment of Swiss companies.
Full-stack implementation experience across AI APIs, retrieval, agents, data pipelines, frontend UX, and production deployment.
Architecture-first approach with evaluation, observability, security, and maintainability designed from the beginning.
Practical project scoping that starts with a pilot and expands only when measurable value is clear.
Custom AI should be narrower than people think
The best first custom AI project usually solves one expensive workflow very well. Narrow scope makes evaluation possible, reduces risk, and gives your team a system they can trust before expanding into broader automation.
Typical systems
Examples include AI assistants grounded in internal knowledge, document processing pipelines, AI features inside SaaS products, workflow copilots, multimodal analysis tools, and systems that connect AI models to ERP, CRM, or domain-specific software.
Evaluation is part of the product
A custom AI system should not rely on gut feeling. It needs test sets, source checks, structured outputs, human review where needed, and monitoring so quality can be improved over time.
When custom AI is the right path
- Generic tools cannot access the right data or workflow context.
- You need reliable structured outputs, citations, or tool actions.
- Your product needs AI features that become part of the user experience.
- The business case is specific enough that a focused pilot can prove value.
Common Questions
How large should the first project be?
The first project should usually be a focused pilot around one workflow, one user group, and one measurable success criterion.
Can you integrate with existing software?
Yes. Custom AI systems often create the most value when they connect to existing documents, databases, APIs, and internal tools.
Which models do you use?
The model choice depends on the task, privacy constraints, cost, latency, and reliability needs. Fanktank can work with OpenAI, Anthropic, Google, open-source models, and retrieval architectures where appropriate.